Presenting an Investment Decision-Making Model in the Financing Market Considering Information Distortion (A Case Study of Knowledge-Based Companies)
Keywords:
Investment decision-making model, financing market, information distortion, grounded theoryAbstract
This study aims to present an investment decision-making model in the financing market by considering information distortion and identifying causal, contextual, and intervening conditions in knowledge-based companies. The research employs a mixed-methods approach (qualitative and quantitative). In the qualitative phase, the statistical population comprised theoretical experts (university faculty members) and experiential experts; 17 participants were selected through snowball sampling, and data were collected via in-depth interviews. In the quantitative phase, the statistical population consisted of accountants and auditors. Qualitative data were analyzed using grounded theory with open, axial, and selective coding, while quantitative data were analyzed using the Partial Least Squares (PLS) method. The findings indicate that analysis of the interviews yielded 239 initial concepts, which were ultimately condensed into 84 subcomponents and 12 main categories, organized within six paradigms: causal conditions (organizational and individual pressures, structural and legal weaknesses), contextual conditions (economic and financial environment, organizational characteristics), intervening conditions (reporting system, characteristics of investors and analysts), the core category (information distortion), strategies, and outcomes. Quantitative results also confirmed the relationships among these factors and the role of information distortion in investment decision-making. Information distortion in knowledge-based companies is shaped by environmental, organizational, and individual factors and can significantly influence investment decisions. Identifying these factors can help improve investors’ decision-making processes and reduce risks arising from non-transparent information.
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Copyright (c) 2025 Farzad Ravand (Author); Ehsan Rahmaninia; Ali Akbar Chaharmahali (Author)
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